Nathaniel Korda
- Artificial Intelligence
- Management Science and Operations Research top 10%
- Computer Networks and Communications
- Computational Theory and Mathematics
- Electrical and Electronic Engineering
- Topics
- Advanced Bandit Algorithms Research (6 papers)Reinforcement Learning in Robotics (3 papers)Stochastic Gradient Optimization Techniques (2 papers)
- Cited by
- Management Science and Operations ResearchArtificial IntelligenceComputer Networks and Communications
- Journals
- Machine LearningarXiv (Cornell University)International Conference on Machine Learning
- Partner nations
- FranceUnited KingdomIndia
In The Last Decade
Nathaniel Korda
5 papers receiving 52 citations
Peers
Comparison fields: 5 of 17
- Artificial Intelligence 48
- Management Science and Operations Research 40
- Computer Networks and Communications 15
- Computational Theory and Mathematics 6
- Electrical and Electronic Engineering 5
Countries citing papers authored by Nathaniel Korda
This map shows the geographic impact of Nathaniel Korda's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Nathaniel Korda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nathaniel Korda more than expected).
Fields of papers citing papers by Nathaniel Korda
This network shows the impact of papers produced by Nathaniel Korda. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Nathaniel Korda. The network helps show where Nathaniel Korda may publish in the future.
Co-authorship network of co-authors of Nathaniel Korda
This figure shows the co-authorship network connecting the top 25 collaborators of Nathaniel Korda. A scholar is included among the top collaborators of Nathaniel Korda based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nathaniel Korda. Nathaniel Korda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | On TD(0) with function approximation: Concentration bounds and a centered variant with exponential convergence | 9 |
| 3 | Online gradient descent for least squares regression: Non-asymptotic bounds and application to bandits. | 1 |
| 4 | Finite-Time Analysis of Kernelised Contextual Bandits | 2 |
| 5 | 28 | |
| 6 | Thompson Sampling: An Optimal Finite Time Analysis | 10 |
About Nathaniel Korda
Nathaniel Korda is a scholar working on Management Science and Operations Research, Artificial Intelligence and Computational Mechanics, having authored 6 papers that have together received 57 indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (6 papers), Reinforcement Learning in Robotics (3 papers) and Stochastic Gradient Optimization Techniques (2 papers). The work is most often cited by research in Management Science and Operations Research (40 citations), Artificial Intelligence (48 citations) and Computer Networks and Communications (15 citations). Nathaniel Korda has collaborated with scholars based in France, United Kingdom and India. Frequent co-authors include Emilie Kaufmann, Rémi Munos, L. A. Prashanth, Rémi Munos and Ilias Flaounas. Their work appears in journals such as Machine Learning, arXiv (Cornell University) and International Conference on Machine Learning.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.